Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations
Cosmos-Transfer2.5, built on top of Cosmos-Predict2.5, produces high-quality world simulations conditioned on multiple spatial control inputs.
A library for differentiable nonlinear optimization
Differentiable rendering without approximation.
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization
Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations
Cosmos-Transfer2.5, built on top of Cosmos-Predict2.5, produces high-quality world simulations conditioned on multiple spatial control inputs.
A library for differentiable nonlinear optimization
Differentiable rendering without approximation.
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization
Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations
Cosmos-Transfer2.5, built on top of Cosmos-Predict2.5, produces high-quality world simulations conditioned on multiple spatial control inputs.
A library for differentiable nonlinear optimization
Differentiable rendering without approximation.
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization
Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.
Skill ディレクトリ
すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations
Cosmos-Transfer2.5, built on top of Cosmos-Predict2.5, produces high-quality world simulations conditioned on multiple spatial control inputs.
A library for differentiable nonlinear optimization
Differentiable rendering without approximation.
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
PyNeuraLogic lets you use Python to create Differentiable Logic Programs
A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization
Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.